sse_within: Calculates Sum of Squared Error in each cluster

In tidyclust: A Common API to Clustering

Calculates Sum of Squared Error in each cluster

Description

Calculates Sum of Squared Error in each cluster

Usage

sse_within(
  object,
  new_data = NULL,
  dist_fun = function(x, y) {
     philentropy::dist_many_many(x, y, method =
    "euclidean")
 }
)

Arguments

object	A fitted kmeans tidyclust model
new_data	A dataset to predict on. If NULL, uses trained clustering.
dist_fun	A function for calculating distances to centroids. Defaults to Euclidean distance on processed data.

Details

sse_within_total() is the corresponding cluster metric function that returns the sum of the values given by sse_within().

Value

A tibble with two columns, the cluster name and the SSE within that cluster.

Examples

kmeans_spec <- k_means(num_clusters = 5) %>%
  set_engine("stats")

kmeans_fit <- fit(kmeans_spec, ~., mtcars)

sse_within(kmeans_fit)

tidyclust documentation built on April 11, 2025, 5:47 p.m.